The On-Line Processing of Verb-Phrase Ellipsis in Aphasia
Bibliographic record
Abstract
We investigate the on-line processing of verb-phrase ellipsis (VPE) constructions in two brain injured populations: Broca's and Anomic aphasics. VPE constructions are built from two simple clauses; the first is the antecedent clause and the second is the ellipsis clause. The ellipsis clause is missing its verb and object (i.e., its verb phrase (VP)), which receives its reference from the fully specified VP in the antecedent clause. VPE constructions are unlike other sentence types that require displacement of an argument NP; these latter constructions (e.g., object-relatives, wh-questions) yield either on-time or delayed antecedent reactivation. Our results demonstrate that Anomics, like unimpaired individuals, evince reactivation of the direct object NP (within the VP) at the elided position. Broca's patients, on the other hand, do not show reactivation of the antecedent. We consider several interpretations for our data, including explanations focusing on the larger 'grain size' of the reconstructed material in the ellipsis clause, the properties of the auxiliary that carries tense and agreement features, and the possibility that the cost-free syntactic copy procedure claimed to underlie VPE may be modulated by the functional deficit in Broca's aphasia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".